A cross-national diagnosis of infodemics: comparing the topical and temporal features of misinformation around COVID-19 in China, India, the US, Germany and France

Understanding the rationales and information environments for early, late, and nonadopters of the COVID-19 vaccine

Anti-vaccine sentiment during the COVID-19 pandemic grew at an alarming rate, leaving much to understand about the relationship between people's vaccination status and the information they were exposed to. This study investigated the relationship between vaccine behavior, decision rationales, and information exposure on social media over time. Using a cohort study that consisted of a nationally representative survey of American adults, three subpopulations (early adopters, late adopters, and nonadopters) were analyzed through a combination of statistical analysis, network analysis, and semi-supervised topic modeling. The main reasons Americans reported choosing to get vaccinated were safety and health. However, work requirements and travel were more important for late adopters than early adopters (95% CI on OR of [0.121, 0.453]). While late adopters' and nonadopters' primary reason for not getting vaccinated was it being too early, late adopters also mentioned safety issues more often and nonadopters mentioned government distrust (95% CI on OR of [0.125, 0.763]). Among those who shared Twitter/X accounts, early adopters and nonadopters followed a larger fraction of highly partisan political accounts compared to late adopters, and late adopters were exposed to more neutral and pro-vaccine messaging than nonadopters. Together, these findings suggest that the decision-making process and the information environments of these subpopulations have notable differences, and any online vaccination campaigns need to consider these differences when attempting to provide accurate vaccine information to all three subpopulations.

A quantitative content analysis of topical characteristics of the online COVID-19 infodemic in the United States and Japan

BACKGROUND

The COVID-19 pandemic has spurred the growth of a global infodemic. In order to combat the COVID-19 infodemic, it is necessary to understand what kinds of misinformation are spreading. Furthermore, various local factors influence how the infodemic manifests in different countries. Therefore, understanding how and why infodemics differ between countries is a matter of interest for public health. This study aims to elucidate and compare the types of COVID-19 misinformation produced from the infodemic in the US and Japan.

METHODS

COVID-19 fact-checking articles were obtained from the two largest publishers of fact-checking articles in each language. 1,743 US articles and 148 Japanese articles in their respective languages were gathered, with articles published between 23 January 2020 and 4 November 2022. Articles were analyzed using the free text mining software KH Coder. Exploration of frequently-occurring words and groups of related words was carried out. Based on agglomeration plots and prior research, eight categories of misinformation were created. Lastly, coding rules were created for these eight categories, and a chi-squared test was performed to compare the two datasets.

RESULTS

Overall, the most frequent words in both languages were related to health-related terms, but the Japan dataset had more words referring to foreign countries. Among the eight categories, differences with chi-squared p ≤ 0.01 were found after Holm-Bonferroni p value adjustment for the proportions of misinformation regarding statistics (US 40.0% vs. JP 25.7%, ϕ 0.0792); origin of the virus and resultant discrimination (US 7.0% vs. JP 20.3%, ϕ 0.1311); and COVID-19 disease severity, treatment, or testing (US 32.6% vs. JP 45.9%, ϕ 0.0756).

CONCLUSIONS

Local contextual factors were found that likely influenced the infodemic in both countries; representations of these factors include societal polarization in the US and the HPV vaccine scare in Japan. It is possible that Japan's relative resistance to misinformation affects the kinds of misinformation consumed, directing attention away from conspiracy theories and towards health-related issues. However, more studies need to be done to verify whether misinformation resistance affects misinformation consumption patterns this way.

A multilingual analysis of pro Russian misinformation on Twitter during the Russian invasion of Ukraine

The Russian government has long since engaged in an information campaign of propaganda and disinformation as a major part of foreign policy. This has been taken to new heights since the invasion of Ukraine in February 2022. In this study, we investigate pro-Russian misinformation within the opening weeks of the invasion in 6 languages: English, Japanese, Spanish, French, German, and Korean. Using Twitter data, we apply a combination of network and language embedding models to identify popular topics of misinformation amongst users in each language. Despite English users forming the most dominant language base on Twitter, we find that the popularity of misinformation in Japanese regularly outstrips English for certain topics. Misinformation shared by Spanish users is also over-represented in proportion to its much smaller user base. Our results provide insight into the current state of misinformation in each language. While we discuss some of the possible drivers behind the factors such as language over-representation, our study also highlights the need for further cross-lingual misinformation research in order to better understand this phenomena in a truly global context.

COVID-19 vaccine-related misinformation identification among Chinese residents during a regional outbreak

Objectives

Misinformation about the COVID vaccines poses a significant challenge to vaccination efforts in many countries. This study examined Chinese citizens' ability to correctly identify COVID-19 vaccine misinformation in geographic areas with and without a regional outbreak. We also investigated the associations between misinformation identification and information source usage, source trust, perceived information quality, and demographic characteristics.

Setting

The online survey was conducted in four cities from June 8th to 15th, 2021 in Guangdong Province, two of which were experiencing a regional surge of COVID-19 delta variant infections, and four cities in Hunan Province, a neighboring province largely unaffected.

Participants

A total of 4,479 individuals aged 18 and above completed the online questionnaire. Given survey length, those who finished the study under 5 min were excluded, resulting in a final sample of 3,800.

Outcome measurements

Misinformation identification, source exposure, source trust, and perceived information quality.

Results

Results showed slightly higher levels of correct misinformation identification in surge vs. non-surge areas. Trust in official information sources was positively associated with correct misinformation identification in full sample analysis, while trust in informal sources was negatively associated with the same outcome. Perceived information quality was positively associated with correct misinformation identification in the full sample.

Conclusion

Information providers in China should enhance the quality of the vaccine information they provide, and the Chinese public should balance their usage of different sources of information to acquire vaccine knowledge.

Protecting public's wellbeing against COVID-19 infodemic: The role of trust in information sources and rapid dissemination and transparency of information over time

Objectives

This study examined how trust in the information about COVID-19 from social media and official media as well as how the information was disseminated affect public's wellbeing directly and indirectly through perceived safety over time.

Methods

Two online surveys were conducted in China, with the first survey (Time1, N = 22,718) being at the early stage of the pandemic outbreak and the second one (Time 2, N = 2,901) two and a half years later during the zero-COVID policy lockdown period. Key measured variables include trust in official media and social media, perceived rapid dissemination and transparency of COVID-19-related information, perceived safety, and emotional responses toward the pandemic. Data analysis includes descriptive statistical analysis, independent samples t-test, Pearson correlations, and structural equation modeling.

Results

Trust in official media, perceived rapid dissemination and transparency of COVID-19-related information, perceived safety, as well as positive emotional response toward COVID-19 increased over time, while trust in social media and depressive response decreased over time. Trust in social media and official media played different roles in affecting public's wellbeing over time. Trust in social media was positively associated with depressive emotions and negatively associated with positive emotion directly and indirectly through decreased perceived safety at Time 1. However, the negative effect of trust in social media on public's wellbeing was largely decreased at Time 2. In contrast, trust in official media was linked to reduced depressive response and increased positive response directly and indirectly through perceived safety at both times. Rapid dissemination and transparency of COVID-19 information contributed to enhanced trust in official media at both times.

Conclusion

The findings highlight the important role of fostering public trust in official media through rapid dissemination and transparency of information in mitigating the negative impact of COVID-19 infodemic on public's wellbeing over time.

Infection control strategies for healthcare workers during COVID-19 pandemic in German hospitals: A cross-sectional study in march-april 2021

Background

Healthcare workers (HCW) are at risk of getting infected with COVID-19 at work. To prevent such incidents and provide a safe environment in hospitals, comprehensive infection control strategies are necessary. We aimed to collect information on COVID-19 infection control strategies regarding personal protective equipment (PPE), regulations during breaks for HCW and dissemination of pandemic-related information.

Methods

We invited infection control practitioners from 987 randomly selected German hospitals in March-April 2021 to participate in our cross-sectional online survey. We categorized the hospital based on bed capacity (≤499 beds = small; ≥500 beds = large). Fisher's exact test was performed and p < 0.05 defined as statistically significant.

Findings

100 participants completed the questionnaire. Small hospitals were more directive about requiring FFP2 respirators (63%), whereas larger hospitals more often gave their HCW a choice between these and medical masks (67%). For the care of COVID-19 and suspected COVID-19 cases, >90% of the participants recommended the use of gloves. Notably, gloves were recommended beyond COVID-19 in 30% of the hospitals. During meal breaks various strategies were followed.

Conclusion

Recommendations for PPE varied across hospital sizes, which could be due to different assessments of necessity and safety. Regulations during breaks varied strongly which illustrates the need for clear official guidelines.

Learning about informal fallacies and the detection of fake news: An experimental intervention

The philosophical concept of informal fallacies-arguments that fail to provide sufficient support for a claim-is introduced and connected to the topic of fake news detection. We assumed that the ability to identify informal fallacies can be trained and that this ability enables individuals to better distinguish between fake news and real news. We tested these assumptions in a two-group between-participants experiment (N = 116). The two groups participated in a 30-minute-long text-based learning intervention: either about informal fallacies or about fake news. Learning about informal fallacies enhanced participants' ability to identify fallacious arguments one week later. Furthermore, the ability to identify fallacious arguments was associated with a better discernment between real news and fake news. Participants in the informal fallacy intervention group and the fake news intervention group performed equally well on the news discernment task. The contribution of (identifying) informal fallacies for research and practice is discussed.

“Masks do not work”: COVID-19 misperceptions and theory-driven corrective strategies on Facebook

Purpose

One of the most prolific areas of misinformation research is examining corrective strategies in messaging. The main purposes of the current study are to examine the effects of (1) partisan media (2) credibility perceptions and emotional reactions and (3) theory driven corrective messages on people's misperceptions about COVID-19 mask wearing behaviors.

Design/methodology/approach

The authors used a randomized experimental design to test the hypotheses. The data were collected via the survey firm Lucid. The number of participants was 485. The study was conducted using Qualtrics after the research project was exempt by the Institutional Research Board of a large University in the US. The authors conducted an online experiment with four conditions, narrative versus statistics and individual versus collective. The manipulation messages were constructed as screenshots from Facebook.

Findings

The findings of this study show that higher exposure to liberal media was associated with lower misperceptions, whereas higher credibility perceptions of and positive reactions toward the misinformation post and negative emotions toward the correction comment were associated with higher misperceptions. Moreover, the findings showed that participants in the narrative and collective-frame condition had the lowest misperceptions.

Originality/value

The authors tested theory driven misinformation corrective messages to understand the impact of these messages and multiple related variables on misperceptions about COVID-19 mask wearing. This study contributes to the existing misinformation correction literature by investigating the explanatory power of the two well-established media effects theories on misinformation correction messaging and by identifying essential individual characteristics that should be considered when evaluating how misperceptions about the COVID-19 crisis works and gets reduced.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2021-0600

How Official Social Media Affected the Infodemic among Adults during the First Wave of COVID-19 in China

The COVID-19 pandemic has demonstrated that social media can impact society both positively (e.g., keeping citizens connected and informed) and negatively (e.g., the deliberate spreading of misinformation). This study aims to examine the underlying mechanisms of the relationship between official social media accounts and the infodemic, experienced during the first wave of COVID-19 in China. A theoretical model is proposed to examine how official social media accounts affected the infodemic during this period. In total, 1398 questionnaire responses were collected via WeChat and Tencent QQ, two leading Chinese social media platforms. Data analysis was conducted using Partial Lease Squares Structural Equation Modeling (PLS-SEM), moderation effect analysis, and mediation effect analysis. Results indicate that the Information Quality (IQ) of Official social media accounts (β = −0.294, p < 0.001) has a significant negative effect on the infodemic. Mediation effect analysis revealed that both social support (β = −0.333, 95% Boot CI (−0.388, −0.280)) and information cascades (β = −0.189, 95% Boot CI (−0.227, −0.151)) mediate the relationship between IQ and the infodemic. Moderation effect analysis shows that private social media usage (F = 85.637, p < 0.001) positively moderates the relationship between IQ and the infodemic, while health literacy has a small negative moderation effect on the relationship between IQ and the infodemic. Our findings show that, in the context of Chinese media, official social media accounts act as a major source of information for influencing the infodemic through increasing social support and reducing information cascades for citizens.

Delineating privacy aspects of COVID tracing applications embedded with proximity measurement technologies & digital technologies

As the COVID-19 pandemic expanded over the globe, governments implemented a series of technological measures to prevent the disease's spread. The development of the COVID Tracing Application (CTA) was one of these measures. In this study, we employed bibliometric and topic-based content analysis to determine the most significant entities and research topics. Additionally, we identified significant privacy concerns posed by CTAs, which gather, store, and analyze data in partnership with large technology corporations using proximity measurement technologies, artificial intelligence, and blockchain. We examined a series of key privacy threats identified in our study. These privacy risks include anti-democratic and discriminatory behaviors, politicization of care, derogation of human rights, techno governance, citizen distrust and refusal to adopt, citizen surveillance, and mandatory legislation of the apps' installation. Finally, sixteen research gaps were identified. Then, based on the identified theoretical gaps, we recommended fourteen prospective study strands. Theoretically, this study contributes to the growing body of knowledge about the privacy of mobile health applications that are embedded with cutting-edge technologies and are employed during global pandemics.

Understanding the “infodemic”: social media news use, homogeneous online discussion, self-perceived media literacy and misperceptions about COVID-19

Purpose

This study has three main purposes: (1) to investigate the association between social media news use and misperceptions about COVID-19; (2) to explore the mediating role of homogeneous online discussion; (3) and to understand whether the extent to which one perceives themselves as media-literate could moderate the relationship.

Design/methodology/approach

The authors conducted an online survey and collected data through Amazon Mechanical Turk. A total of 797 participants aged 18 and above completed the survey. The average age of the respondents is 38.40 years (SD = 12.31), and 41.2% were female. In terms of party identification, 30.8% were reported leaning toward Republicans; 53.7% leaned toward Democrats, and 15.4% were reported neutral.

Findings

Results from a moderated mediation model show that social media news use is positively associated with misperceptions about the COVID-19. Moreover, homogeneous online discussion was a significant mediator of the relationship between social media news use and misperceptions about COVID-19. Further, self-perceived media literacy (SPML) significantly moderated the main and indirect effects between social media news use and COVID-19 misperceptions, such that the associations became weaker among those with higher SPML.

Originality/value

Findings provide insights into the significance of online information sources, discussion network heterogeneity and media literacy education. Although there have been many studies on misinformation, prior research has not examined these relationships, which may help provide solutions to cope with misinformation.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2021-0305

#CoronaVirus and public health: the role of social media in sharing health information

Purpose

The purpose of this study is to examine how factual information and misinformation are being shared on Twitter by identifying types of social media users who initiate the information diffusion process.

Design/methodology/approach

This study used a mixed methodology approach to analyze tweets with COVID-19-related hashtags. First, a social network analysis was conducted to identify social media users who initiate the information diffusion process, followed by a quantitative content analysis of tweets by users with more than 5K retweets to identify what COVID-19 claims, factual information, misinformation and disinformation was shared on Twitter.

Findings

Results found very little misinformation and disinformation distributed widely. While health experts and journalists shared factual COVID-19-related information, they were not receiving optimum engagement. Tweets by citizens focusing on personal experience or opinions received more retweets and likes compared to any other sender type. Similarly, celebrities received more replies than any other sender type.

Practical implications

This study helps medical experts and government agencies understand the type of COVID-19 content and communication being shared on social media for population health purposes.

Originality/value

This study offers insight into how social media users engage with COVID-19-related information on Twitter and offers a typology of categories of information shared about the pandemic.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2021-0143/.

The impact of the COVID-19 pandemic on the creative industries: A literature review and future research agenda

The ongoing COVID-19 pandemic has affected countless businesses, leading to serious disruptions for many industries. Drawing on the resilience literature, this study offers an understanding of the impact of the COVID-19 pandemic on the creative industries and their response to the challenges they have encountered. This study reviews 59 papers following the systematic literature review approach and reveals several positive implications of the COVID-19 pandemic within the creative industries (e.g., IT and software) as well as the negative (the music industry, festivals, cultural events). Identifying six themes related to the impact of the COVID-19 pandemic on the creative industries, we develop a response matrix based on the discussion of firms' digital capabilities and their ability to adapt to the COVID-19 crisis. We outline future research directions using a Theory-Context-Characteristics-Methodology (TCCM) framework.

Exploring how online responses change in response to debunking messages about COVID-19 on WhatsApp

Purpose

The COVID-19 pandemic has spurred a concurrent outbreak of false information online. Debunking false information about a health crisis is critical as misinformation can trigger protests or panic, which necessitates a better understanding of it. This exploratory study examined the effects of debunking messages on a COVID-19-related public chat on WhatsApp in Singapore.

Design/methodology/approach

To understand the effects of debunking messages about COVID-19 on WhatsApp conversations, the following was studied. The relationship between source credibility (i.e. characteristics of a communicator that affect the receiver's acceptance of the message) of different debunking message types and their effects on the length of the conversation, sentiments towards various aspects of a crisis, and the information distortions in a message thread were studied. Deep learning techniques, knowledge graphs (KG), and content analyses were used to perform aspect-based sentiment analysis (ABSA) of the messages and measure information distortion.

Findings

Debunking messages with higher source credibility (e.g. providing evidence from authoritative sources like health authorities) help close a discussion thread earlier. Shifts in sentiments towards some aspects of the crisis highlight the value of ABSA in monitoring the effectiveness of debunking messages. Finally, debunking messages with lower source credibility (e.g. stating that the information is false without any substantiation) are likely to increase information distortion in conversation threads.

Originality/value

The study supports the importance of source credibility in debunking and an ABSA approach in analysing the effect of debunking messages during a health crisis, which have practical value for public agencies during a health crisis. Studying differences in the source credibility of debunking messages on WhatsApp is a novel shift from the existing approaches. Additionally, a novel approach to measuring information distortion using KGs was used to shed insights on how debunking can reduce information distortions.

The Active Role of the Internet and Social Media Use in Nonpharmaceutical and Pharmaceutical Preventive Measures against COVID-19

During the COVID-19 pandemic, does more internet and social media use lead to taking more- or less-effective preventive measures against the disease? A two-wave longitudinal survey with the general population in mainland China in mid-2020 found that during the COVID-19 pandemic, internet and social media use intensity promoted the adoption of nonpharmaceutical and pharmaceutical antipandemic measures. The first wave of data (n = 1014) showed that the more intensively people used the internet/social media, the more they perceived the threat of the pandemic, and took more nonpharmaceutical preventive measures (e.g., wearing masks, maintaining social distance, and washing hands) as a result. The second wave (n = 220) showed firstly the predicted relationship between internet/social media use intensity and the perceived threat of the pandemic and the adoption of nonpharmaceutical preventive measures by cross-lagged analysis; secondly, the predictive effect of internet/social media use on the adoption of pharmacological measures (i.e., willingness to vaccinate against COVID-19) and the mediating role of perceived pandemic threat were verified. The article concludes with a discussion of the role of the internet and social media use in the fight against COVID-19 in specific macrosocial contexts.

Why Do Citizens Share COVID-19 Fact-Checks Posted by Chinese Government Social Media Accounts? The Elaboration Likelihood Model

Widespread misinformation about COVID-19 poses a significant threat to citizens long-term health and the combating of the disease. To fight the spread of misinformation, Chinese governments have used official social media accounts to participate in fact-checking activities. This study aims to investigate why citizens share fact-checks about COVID-19 and how to promote this activity. Based on the elaboration likelihood model, we explore the effects of peripheral cues (social media capital, social media strategy, media richness, and source credibility) and central cues (content theme and content importance) on the number of shares of fact-checks posted by official Chinese Government social media accounts. In total, 820 COVID-19 fact-checks from 413 Chinese Government Sina Weibo accounts were obtained and evaluated. Results show that both peripheral and central cues play important roles in the sharing of fact-checks. For peripheral cues, social media capital and media richness significantly promote the number of shares. Compared with the push strategy, both the pull strategy and networking strategy facilitate greater fact-check sharing. Fact-checks posted by Central Government social media accounts receive more shares than local government accounts. For central cues, content importance positively predicts the number of shares. In comparison to fact-checks about the latest COVID-19 news, government actions received fewer shares, while social conditions received more shares.

Text Analysis Methods for Misinformation–Related Research on Finnish Language Twitter

The dissemination of disinformation and fabricated content on social media is growing. Yet little is known of what the functional Twitter data analysis methods are for languages (such as Finnish) that include word formation with endings and word stems together with derivation and compounding. Furthermore, there is a need to understand which themes linked with misinformation—and the concepts related to it—manifest in different countries and language areas in Twitter discourse. To address this issue, this study explores misinformation and its related concepts: disinformation, fake news, and propaganda in Finnish language tweets. We utilized (1) word cloud clustering, (2) topic modeling, and (3) word count analysis and clustering to detect and analyze misinformation-related concepts and themes connected to those concepts in Finnish language Twitter discussions. Our results are two-fold: (1) those concerning the functional data analysis methods and (2) those about the themes connected in discourse to the misinformation-related concepts. We noticed that each utilized method individually has critical limitations, especially all the automated analysis methods processing for the Finnish language, yet when combined they bring value to the analysis. Moreover, we discovered that politics, both internal and external, are prominent in the Twitter discussions in connection with misinformation and its related concepts of disinformation, fake news, and propaganda.